There is a problem that environmental noise deteriorates speech recognition performance in a practical environment.
As a method for solving this problem, a spectrum subtraction method has been disclosed in, e.g., S. F. Boll, “Suppression of Acoustic Noise in Speech Using Spectral Subtraction,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. ASSP-27, No. 2, pp. 113-120, 1979. This is a method to reduce the spectral effects of acoustically added noise in speech by subtracting an estimated noise from an input speech.
This method decides a noise subtraction rate with a noise suppression coefficient. The coefficient should be large in order to make the influence of noise smaller, but an unduly large coefficient distorts the subtracted speech and deteriorates the speech recognition performance. The optimal coefficient should be determined according to the amplitude of the added noise. However, the noise amplitude changes frequently in a practical environment, so it is very difficult to determine the optimal coefficient.
In order to solve this problem, the method to vary the noise suppression coefficient according to the SNR between speech and noise is proposed. The method is disclosed in, e.g., Japan Patent Application KOKAI No. 2000-330597.
This method works well, if the environmental noise changes slowly. But there are some bursts of noise like honking horns in a practical environment. In those cases, it becomes very difficult to estimate an accurate SNR and to determine the optimal noise suppression coefficient. An inaccurate noise suppression coefficient could deteriorate the performance of speech recognition.
Thus the conventional methods have a problem of insufficient noise subtraction in a practical environment. That causes a problem not to obtain sufficient speech recognition performance.